Study on Threshold Method in Gene Recognition

Tian  Jiu Leng; Li Qiong Tang

doi:10.4028/www.scientific.net/AMM.651-653.2201

Paper Titles

Research and Simulation of Data Mining Method Based on the Association Rules Algorithm
p.2185

Research on Gridding Algorithm of Remote Sensing Image Segmentation by Region Growth
p.2189

Riemann Integrablity of the Composite Function
p.2193

Simhash for Large Scale Image Retrieval
p.2197

Study on Threshold Method in Gene Recognition
p.2201

Sufficient Conditions of H-Matrix
p.2207

The Equivalence Relationship of Matrix and the Corresponding Equivalence Classes
p.2211

The Identity between the Real Number and Order one Matrix
p.2216

The Image Fusion Algorithm Based on Rough Neural Network
p.2220

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 651-653Study on Threshold Method in Gene Recognition

Study on Threshold Method in Gene Recognition

Abstract:

This paper mainly researches the deterministic methods that discriminating threshold by signal noise ration of different kinds of genes, approaches the relation between frequency spectrum and signal noise ration under Voss mapping and Z-curve mapping, and concludes the deterministic methods and threshold results of different kinds of gene thresholds.

You might also be interested in these eBooks

Material Science, Civil Engineering and Architecture Science, Mechanical Engineering and Manufacturing Technology II

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 651-653)

Pages:

2201-2206

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.651-653.2201

Citation:

Cite this paper

Online since:

September 2014

Authors:

Tian Jiu Leng*, Li Qiong Tang

Keywords:

Frequency Spectrum, Gene Recognition, Signal Noise Ration, Threshold

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Zhang R, Zhang C T. Z curves, an intuitive tool for visualing and analyzing the DNA sequences. J Biomol Struct Dyn., 11: 767-782. (1994).

Google Scholar

[2] Yutao Ma, Jing Ce, Daming Liu, Power spectrum density analysis of the protein coding region predicted based on Fu Liye calculation method , Journal of Ningxia University(Natural Science Edition), 32(2)134-138, (2011).

Google Scholar

[3] Burge, C., Karlin, S., 1997. Prediction of complete gene structures in human genomic DNA. J. Mol. Biol. 268, 78–94.

DOI: 10.1006/jmbi.1997.0951

Google Scholar

[4] Yin, C., Yau, S.S. -T. 2007. Prediction of protein coding regions by the 3-base periodicity analysis of a DNA sequence. Journal of Theoretical Biology. 247, 687–694.

DOI: 10.1016/j.jtbi.2007.03.038

Google Scholar

[5] Ceng Jianjun, Li Shihang and other. MATLAB language and mathematical modeling, Hefei: Anhui University press, (2005).

Google Scholar